Evaluating reproducibility of AI algorithms in digital pathology with DAPPER A Bizzego, N Bussola, M Chierici, V Maggio, M Francescatto, L Cima, ... PLoS computational biology 15 (3), e1006269, 2019 | 67 | 2019 |
Integrating deep and radiomics features in cancer bioimaging A Bizzego, N Bussola, D Salvalai, M Chierici, V Maggio, G Jurman, ... 2019 IEEE Conference on Computational Intelligence in Bioinformatics and …, 2019 | 56 | 2019 |
Integrative network fusion: a multi-omics approach in molecular profiling M Chierici, N Bussola, A Marcolini, M Francescatto, A Zandonà, ... Frontiers in oncology 10, 1065, 2020 | 48 | 2020 |
AI slipping on tiles: Data leakage in digital pathology N Bussola, A Marcolini, V Maggio, G Jurman, C Furlanello International Conference on Pattern Recognition, 167-182, 2021 | 40 | 2021 |
Predictability of drug-induced liver injury by machine learning M Chierici, M Francescatto, N Bussola, G Jurman, C Furlanello Biology direct 15, 1-10, 2020 | 38 | 2020 |
histolab: A Python library for reproducible Digital Pathology preprocessing with automated testing A Marcolini, N Bussola, E Arbitrio, M Amgad, G Jurman, C Furlanello SoftwareX 20, 101237, 2022 | 25 | 2022 |
Machine learning models for predicting endocrine disruption potential of environmental chemicals M Chierici, M Giulini, N Bussola, G Jurman, C Furlanello Journal of Environmental Science and Health, Part C 36 (4), 237-251, 2018 | 12 | 2018 |
Towards a scientific blockchain framework for reproducible data analysis C Furlanello, M De Domenico, G Jurman, N Bussola arXiv preprint arXiv:1707.06552, 2017 | 11 | 2017 |
Quantification of the immune content in neuroblastoma: Deep learning and topological data analysis in digital pathology N Bussola, B Papa, O Melaiu, A Castellano, D Fruci, G Jurman International Journal of Molecular Sciences 22 (16), 8804, 2021 | 10 | 2021 |
A weakly supervised deep learning framework for whole slide classification to facilitate digital pathology in animal study N Bussola, J Xu, L Wu, L Gorini, Y Zhang, C Furlanello, W Tong Chemical Research in Toxicology 36 (8), 1321-1331, 2023 | 9 | 2023 |
Evolving educational landscape in pathology: a comprehensive bibliometric and visual analysis including digital teaching and learning resources L Cima, N Bussola, LA Hassell, TR Kiehl, C Schukow, N Zerbe, E Munari, ... Journal of clinical pathology 77 (2), 87-95, 2024 | 7 | 2024 |
Not again! Data leakage in digital pathology N Bussola, A Marcolini, V Maggio, G Jurman, C Furlanello arXiv, 2019 | 7 | 2019 |
Cyst segmentation on kidney tubules by means of U-Net deep-learning models S Monaco, N Bussola, S Butto, D Sona, D Apiletti, G Jurman, E Viola, ... 2021 IEEE International Conference on Big Data (Big Data), 3923-3926, 2021 | 6 | 2021 |
Visceral Adiposity and Progression of ADPKD: A Cohort Study of Patients from the TEMPO 3: 4 Trial KL Nowak, F Moretti, N Bussola, CN Steele, AV Gregory, TL Kline, ... American Journal of Kidney Diseases, 2024 | 5 | 2024 |
The development of artificial intelligence in the histological diagnosis of Inflammatory Bowel Disease (IBD-AI) C Furlanello, N Bussola, N Merzi, GP Trapletti, M Cadei, R Del Sordo, ... Digestive and Liver Disease 57 (1), 184-189, 2025 | 3 | 2025 |
AI models for automated segmentation of engineered polycystic kidney tubules S Monaco, N Bussola, S Buttò, D Sona, F Giobergia, G Jurman, C Xinaris, ... Scientific Reports 14 (1), 2847, 2024 | 3 | 2024 |
Author Correction: AI models for automated segmentation of engineered polycystic kidney tubules S Monaco, N Bussola, S Buttò, D Sona, F Giobergia, G Jurman, C Xinaris, ... Scientific Reports 14, 2024 | | 2024 |
AI for Omics and Imaging Models in Precision Medicine and Toxicology N Bussola Università degli studi di Trento, 2022 | | 2022 |